On June 4 and 17, 2011, separate oil spill accidents occurred at two oil platforms in the Bohai Sea, China. The oil spills were subsequently observed on different types of satellite images including SAR (Synthetic Aperture Radar), Chinese HJ-1-B CCD and NASA MODIS. To illustrate the fate of the oil spills, we performed two numerical simulations to simulate the trajectories of the oil spills with the GNOME (General NOAA Operational Modeling Environment) model. For the first time, we drive the GNOME with currents obtained from an operational ocean model (NCOM, Navy Coastal Ocean Model) and surface winds from operational scatterometer measurements (ASCAT, the Advanced Scatterometer). Both data sets are freely and openly available. The initial oil spill location inputs to the model are based on the detected oil spill locations from the SAR images acquired on June 11 and 14. Three oil slicks are tracked simultaneously and our results show good agreement between model simulations and subsequent satellite observations in the semi-enclosed shallow sea. Moreover, GNOME simulation shows that the number of ‘splots’, which denotes the extent of spilled oil, is a vital factor for GNOME running stability when the number is less than 500. Therefore, oil spill area information obtained from satellite sensors, especially SAR, is an important factor for setting up the initial model conditions.

Atmospheric concentrations of elemental, organic and water–soluble organic carbon (EC, OC and WSOC) and polycyclic aromatic hydrocarbons (PAHs) have been studied in PM2.5 (particulate matter of aerodynamic diameter ≤2.5 μm) from a site (Barapani: 25.7 °N; 91.9 °E; 1 064 m amsl) in the foot–hills of NE–Himalaya (NE–H). Under favorable wind–regimes, during the wintertime (January–March), study region is influenced by the long–range transport of aerosols from the Indo–Gangetic Plain (IGP). For rest of the year, ambient atmosphere over the NE–H is relatively clean due to frequent precipitation events associated with the SW– and NE–monsoon. The concentration of PM2.5 over NE–H, during the wintertime, varied from 39–348 μg m–3, with average contribution of OC and EC as 36±8% (AVG±SD) and 6±3%, respectively. For the OC/EC ratio as high as 10–15 (relatively high compared to fossil–fuel source) associated with WSOC/OC ratio exceeding 0.5 in NE–H, it can be inferred that dominant source of carbonaceous aerosols is attributable to biomass burning emissions and/or contributions from secondary organic aerosols (SOA). The OC/PM2.5 ratio from NE–H is somewhat higher compared to upwind regions in the IGP (Range: 0.16–0.24). The abundance of ΣPAHs show large variability, ranging from 4–46 ng m–3, and the ratio of sum of 4– to 6–ring PAHs (Σ(4– to 6–) PAHs) to EC is 2.4 mg g–1; similar to that in the upwind IGP and is about a factor of two higher than that from the fossil–fuel combustion sources. The cross-plot of PAH isomers [FLA/(FLA+PYR) vs. ANTH/(ANTH+PHEN), BaA/(BaA+CHRY+TRIPH), BaP/(BaP+B[b,j,k]FLA) and IcdP/(IcdP+BghiP)] reaffirms the dominant impact of biomass burning emissions. These results have implications to large temporal variability in aerosol radiative forcing and environmental change over the NE–Himalaya.

Plastic debris on six beaches near the Nakdong River Estuary, South Korea, was sampled in May and September 2012 and classified into three size classes, large microplastics (1–5mm), mesoplastics (5–25mm), and macroplastics (>25mm). The relationships among the abundances of the size classes were then examined. The abundances of each size category in May (before rainy season) and in September (after rainy season) were 8205 and 27,606particles/m2 for large microplastics, 238 and 237particles/m2 for mesoplastics, and 0.97 and 1.03particles/m2 for macroplastics, respectively. Styrofoam was the most abundant item both in microplastic and mesoplastic debris, while intact plastics were most common in macroplastic debris. The abundances of meso- and micro-plastics were the most strongly correlated. There was a higher correlation between the abundances of macro- and meso-plastics than between macro- and micro-plastics.

The aim of this study was to examine the temporal and spatial total column ozone distribution in West Africa using Total Ozone Mapping spectrometer (TOMS) daily data for five years between 2001 and 2005 in fifteen locations. In this study, certain significant observations emerged: weather activity particularly the rainfall producing mechanism (dynamic of the wind systems) was responsible for about 62% ozone distribution in the region. Ozone maximum and minimum concentrations over all the stations were 305 DU and 232 DU respectively producing an average range of 73 DU (only about 27.03% of the mean value). Ozone has a seasonal distribution with minimum occurring during the dry season and maximum occurring during the wet season. A decreasing rate of about –0.6 DU/year was found for the region. Interannual ozone characteristics revealed an oscillating feature similar to Quasi – biennial Oscillation (QBO) footprints which indicated the importance of stratosphere – troposphere exchange to ozone distribution in the region. Furthermore, lag of about one or two months occurs between south (lower latitude) and north (higher latitude) monthly ozone maximums.

Ambient visibility is a complex manifestation arising out of interactions among many atmospheric variables, including ambient aerosol load, and region specific geophysical characteristics. To functionally relate visibility impairment in Delhi region during winter months-months marred with poor visibility conditions–a novel experiment was designed to relate visibility with ambient aerosol load (PM2.5), and relevant meteorological variables: dew point temperature (Dp), height of planetary boundary layer (PBL), ambient temperature (T), relative humidity (RH), wind speed (WS) and wind direction (WD). Time series data sets of Visibility(t) and other variables were subjected to non–linear decomposition using Empirical Mode Decomposition Method (EMD), enabling to obtain total cyclic and acyclic–trend components embedded in all data–sets. Extracted total cyclic visibility components were functionally related with the corresponding components associated with PM2.5 load and meteorological variables. Decomposed acyclic–trend component of the visibility, representing time dependent acyclic trend (AT), was separately related with the corresponding AT components of the considered meteorological variables. The decomposed components of the visibility (total cyclic and AT) were subjected to multiple linear regression to establish a functional relationship between them and a set of variables among the considered variables. The analysis suggests that acyclic–trend associated with Visibility(t) can be predicted better as opposed to the Visibility(t)cyclic component.

Sediment samples were collected from Kallar, Korampallam creek and Punnakayal estuaries of Tuticorin coast for assessing the level of contamination by trace elements in these estuarine sediments. The trace element concentration, calcium carbonate, organic carbon and mercury level were analyzed by Inductively Coupled Plasma Atomic Emission Spectrophotometer, Titrimetric method and SnCl2 reduction method. The results reveals that the enrichment factor, metal pollution index and geo-accumulation index of these estuarine sediments were predominantly polluted by Cd, As, Zn, Hg and Pb. The factor analysis revealed the source of trace element accumulation in the estuarine sediments particularly Mn and Fe are from riverine inputs and As and Hg from untreated industrial effluents. Among the selected estuaries, Korampallam creek was found to be highly contaminated by trace elements due to the discharge of effluents from thermal power plant, Tuticorin alkali chemicals, copper smelting, Petrochemical industries and shipping activities.

Spatial trends of polybrominated diphenyl ether (PBDE) congeners were examined by using high resolution gas chromatography – low resolution electron impact mass spectrometry (GC-EIMS) in 414 samples of young-of-the-year (YOY) bluefish (Pomatomus saltatrix) collected from a total of 29 nursery habitats along the US Atlantic coastline from Massachusetts to Florida. Of the 26 target PBDE congeners, BDE-47 (4 Br), BDE-100 (5 Br), BDE-49 (4 Br), BDE-99 (5 Br), and BDE-154 (6 Br) were the five most frequently detected congeners in the order of decreasing importance. The sum of the concentrations of five major PBDE congeners, referred to as ΣPBDEs, varied between estuaries and also among samples from a given estuary. ΣPBDEs were lowest in YOY bluefish from Vineyard Sound, Nantucket Sound, Great Bay, Delaware Bay, Lynnhaven Bay, Cape Lookout, and Crescent Beach, with maximum ΣPBDE concentrations below 10ng/g wet weight. ΣPBDEs in three bluefish samples from Stamford Harbor were detected at relatively high to unusually high concentrations of 69.1, 205, and 561ng/g wet weight. ΣPBDE values for other Stamford Harbor bluefish were generally low. Highest PBDE concentrations were detected in the vicinity of industrial and urban locations within the New York – New Jersey metropolitan complex. Among them, bluefish from Newark Bay were generally the most contaminated with an average ΣPBDE value of 56.6±30.8ng/g wet weight. ΣPBDEs in bluefish from Newark Bay were numerically greater than ΣPBDEs in bluefish from all locations, however these differences were not statistically significant. Modest to good correlations between ΣPBDEs and lipids were observed for YOY bluefish from Buzzards Bay, Upper New Bedford Harbor, Lower New Bedford Harbor, Outer New Bedford Harbor, Providence Harbor, Housatonic River, Norwalk Harbor, Little Neck Bay, Newark Bay, Sandy Hook Bay, Great Bay, Delaware Bay, Patuxent River and Crescent Beach. Poor correlations between ΣPBDE and lipids were observed for bluefish from other estuaries. ΣPBDEs were not always correlated with fish length or weight. ΣPBDEs in YOY bluefish along the US Atlantic coastline modestly paralleled ΣPBDEs in mussels and oysters, from not exact but geographically loosely similar locations, reported in the NOAA Mussel Watch Program. A number of researchers who used the high resolution mass spectrometry reported additional PBDE congeners. Although PBDE congeners we report do appear to be the prominent congeners in these studies, it is likely that the comparisons will be skewed in certain instances.

Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs.In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement.We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).

We present a global dioxin model that simulates one year of atmospheric emissions, transport processes, and depositions to the earth’s terrestrial and marine habitats. We map starting emission levels for each land area, and we also map the resulting deposits to terrestrial and marine environments. This model confirms that ‘hot spots’ of deposition are likely to be in northern Europe, eastern North America, and in parts of Asia with the highest marine dioxin depositions being the northeast and northwest Atlantic, western Pacific, northern Indian Ocean and the Mediterranean. It also reveals that approximately 40% of airborne dioxin emissions are deposited to marine environments and that many countries in Africa receive more dioxin than they produce, which results in these countries being disproportionately impacted. Since human exposure to dioxin is largely through diet, this work highlights food producing areas that receive higher atmospheric deposits of dioxin than others.

In the framework of the ICON project, environmental genotoxicity and cytotoxicity levels were assessed in blood erythrocytes of dab (Limanda limanda) and haddock (Melanogrammus aeglefinus) collected at 25 stations in the North Sea and near the coast of Iceland in August–October 2008. Micronuclei, nuclear buds and bi-nucleated cells with nucleoplasmic bridges were assessed as environmental genotoxicity biomarkers, and the frequency of fragmented-apoptotic and bi-nucleated erythrocytes were assessed as environmental cytotoxicity biomarkers. The lowest frequencies of genotoxic and cytotoxic abnormalities were detected in fish from the Icelandic study stations. The highest frequencies of abnormalities were recorded in dab from the Dogger Bank and the German Bight, in haddock from the Egersund Bank and from an area off the Firth of Forth (North Sea). In fish from the Icelandic reference area, frequencies of genotoxicity and cytotoxicity responses were significantly lower than in fish from most areas of the North Sea.